"Scentsor": A Whole-Cell Yeast Biosensor with an Olfactory Reporter for Low-Cost and Equipment-Free Detection of Pharmaceuticals

Deep-Learning-Guided Electrochemical Impedance Spectroscopy for Calibration-Free Pharmaceutical Moisture Content Monitoring

The moisture content of pharmaceutical powders can significantly impact the physical and chemical properties of drug formulations, solubility, flowability, and stability. However, current technologies for measuring moisture content in pharmaceutical materials require extensive calibration processes, leading to poor consistency and a lack of speed. To address this challenge, this study explores the feasibility of using impedance spectroscopy to enable accurate, rapid testing of moisture content of pharmaceutical materials with minimal to zero calibration. By utilizing electrochemical impedance spectroscopy (EIS) signals, we identify a strong correlation between the electrical properties of the materials and varying moisture contents in pharmaceutical samples. Equivalent circuit modeling is employed to unravel the underlying mechanism, providing valuable insights into the sensitivity of impedance spectroscopy to moisture content variations. Furthermore, the study incorporates deep learning techniques utilizing a 1D convolutional neural network (1DCNN) model to effectively process the complex spectroscopy data. The proposed model achieved a notable predictive accuracy with an average error of just 0.69% in moisture content estimation. This method serves as a pioneering study in using deep learning to provide a reliable solution for real-time moisture content monitoring, with potential applications extending from pharmaceuticals to the food, energy, environmental, and healthcare sectors.

Development of Nanobody-Displayed Whole-Cell Biosensors for the Colorimetric Detection of SARS-CoV-2

The accurate and effective detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential to preventing the spread of infectious diseases and ensuring human health. Herein, a nanobody-displayed whole-cell biosensor was developed for colorimetric detection of SARS-CoV-2 spike proteins. Serving as bioreceptors, yeast surfaces were genetically engineered to display SARS-CoV-2 binding of llama-derived single-domain antibodies (nanobodies) with high capture efficiency, facilitating the concentration and purification of SARS-CoV-2. Gold nanoparticles (AuNPs) employed as signal transductions were functionalized with horseradish peroxidase (HRP) and anti-SARS monoclonal antibodies to enhance the detection sensitivity. In the presence of SARS-CoV-2 spike proteins, the sandwiched binding will be formed by linking engineered yeast, SARS-CoV-2 spike proteins, and reporter AuNPs. The colorimetric signal was generated by the enzymatic reaction of HRP and its corresponding colorimetric substrate/chromogen system. At the optimal conditions, the developed whole-cell biosensor enables the sensitive detection of SARS-CoV-2 spike proteins in a linear range from 0.01 to 1 μg/mL with a limit of detection (LOD) of 0.037 μg/mL (about 4 × 108 virion particles/mL). Furthermore, the whole-cell biosensor was demonstrated to detect the spike protein of different SARS-CoV-2 variants in human serum, providing new possibilities for the detection of future SARS-CoV-2 variants.

Development of an Efficient FRET-Based Ratiometric Uranium Biosensor

The dispersion of uranium in the environment can pose a problem for the health of humans and other living organisms. It is therefore important to monitor the bioavailable and hence toxic fraction of uranium in the environment, but no efficient measurement methods exist for this. Our study aims to fill this gap by developing a genetically encoded FRET-based ratiometric uranium biosensor. This biosensor was constructed by grafting two fluorescent proteins to both ends of calmodulin, a protein that binds four calcium ions. By modifying the metal-binding sites and the fluorescent proteins, several versions of the biosensor were generated and characterized in vitro. The best combination results in a biosensor that is affine and selective for uranium compared to metals such as calcium or other environmental compounds (sodium, magnesium, chlorine). It has a good dynamic range and should be robust to environmental conditions. In addition, its detection limit is below the uranium limit concentration in drinking water defined by the World Health Organization. This genetically encoded biosensor is a promising tool to develop a uranium whole-cell biosensor. This would make it possible to monitor the bioavailable fraction of uranium in the environment, even in calcium-rich waters.

Synthetic biology-inspired cell engineering in diagnosis, treatment, and drug development

The fast-developing synthetic biology (SB) has provided many genetic tools to reprogram and engineer cells for improved performance, novel functions, and diverse applications. Such cell engineering resources can play a critical role in the research and development of novel therapeutics. However, there are certain limitations and challenges in applying genetically engineered cells in clinical practice. This literature review updates the recent advances in biomedical applications, including diagnosis, treatment, and drug development, of SB-inspired cell engineering. It describes technologies and relevant examples in a clinical and experimental setup that may significantly impact the biomedicine field. At last, this review concludes the results with future directions to optimize the performances of synthetic gene circuits to regulate the therapeutic activities of cell-based tools in specific diseases.

Recent advances in the analytical strategies of microbial biosensor for detection of pollutants

Microbial biosensor which integrates different types of microorganisms, such as bacteria, microalgae, fungi, and virus have become suitable technologies to address limitations of conventional analytical methods. The main applications of biosensors include the detection of environmental pollutants, pathogenic bacteria and compounds related to illness, and food quality. Each type of microorganisms possesses advantages and disadvantages with different mechanisms to detect the analytes of interest. Furthermore, there is an increasing trend in genetic modifications for the development of microbial biosensors due to potential for high-throughput analysis and portability. Many review articles have discussed the applications of microbial biosensor, but many of them focusing only about bacterial-based biosensor although other microbes also possess many advantages. Additionally, reviews on the applications of all microbes as biosensor especially viral and microbial fuel cell biosensors are also still limited. Therefore, this review summarizes all the current applications of bacterial-, microalgal-, fungal-, viral-based biosensor in regard to environmental, food, and medical-related applications. The underlying mechanism of each microbes to detect the analytes are also discussed. Additionally, microbial fuel cell biosensors which have great potential in the future are also discussed. Although many advantageous microbial-based biosensors have been discovered, other areas such as forensic detection, early detection of bacteria or virus species that can lead to pandemics, and others still need further investigation. With that said, microbial-based biosensors have promising potential for vast applications where the biosensing performance of various microorganisms are presented in this review along with future perspectives to resolve problems related on microbial biosensors.

Engineering Saccharomyces cerevisiae-based biosensors for copper detection

Heavy metals, that is Cu(II), are harmful to the environment. There is an increasing demand to develop inexpensive detection methods for heavy metals. Here, we developed a yeast biosensor with reduced‐noise and improved signal output for potential on‐site copper ion detection. The copper‐sensing circuit was achieved by employing a secondary genetic layer to control the galactose‐inducible (GAL) system in Saccharomyces cerevisiae. The reciprocal control of the Gal4 activator and Gal80 repressor under copper‐responsive promoters resulted in a low‐noise and sensitive yeast biosensor for copper ion detection. Furthermore, we developed a betaxanthin‐based colorimetric assay, as well as 2‐phenylethanol and styrene‐based olfactory outputs for the copper ion detection. Notably, our engineered yeast sensor confers a narrow range switch‐like behaviour, which can give a ‘yes/no’ response when coupled with a betaxanthin‐based visual phenotype. Taken together, we envision that the design principle established here might be applicable to develop other sensing systems for various chemical detections.

A low‐noise yeast biosensor was developed for copper detection. The yeast biosensor confers a switch‐like behavior with a “yes/no” response. The olfactory outputs for copper detection were also developed.